Biggus also has such a function:
https://github.com/SciTools/biggus/blob/master/biggus/__init__.py#L2878
It handles newaxis outside of that function in:
https://github.com/SciTools/biggus/blob/master/biggus/__init__.py#L537.
Again, it only aims to deal with orthogonal array indexing, not numpy
Nice idea. Just a repository of courses would be a great first step.
For example, I know Jake Vanderplas's course at
https://github.com/jakevdp/2013_fall_ASTR599 is useful, and I have a few
introduction (3hr) courses at https://github.com/SciTools/courses.
On 3 July 2014 16:59, Chris Barker
I just wanted to let you know that there is currently a vacancy for a
full-time developer at the Met Office, the UK's National Weather Service,
within our Analysis, Visualisation and Data (AVD) team.
I'm posting on this list as the Met Office's AVD team are heavily involved
in the development of
For the record, I started a discussion about 6 months ago about a
find_first type function which avoided running the logic over the whole
array (using lambdas instead). This spilled into a discussion about
implementing a short-cutted any or all function:
I didn't find the rollaxis solution particularly obvious and also had to
think about what rollaxis did before understanding its usefulness for
iteration.
Now that I've understood it, I'm +1 for the statement that, as it stands,
the proposed iteraxis method doesn't add enough to warrant its
, Phil Elson pelson@gmail.com wrote:
Bump.
I'd be interested to know if this is a desirable feature for numpy?
(specifically the 1D find functionality rather than the any/all
also
discussed)
If so, I'd be more than happy to submit a PR, but I don't want to put in
the
effort
.
Cheers,
On 8 March 2013 17:38, Phil Elson pelson@gmail.com wrote:
Interesting. I hadn't thought of those. I've implemented (very roughly
without a sound logic check) and benchmarked:
def my_any(a, predicate, chunk_size=2048):
try:
next(find(a, predicate, chunk_size
my_all(a, lambda a: np.abs(a) 1)
1 loops, best of 3: 73.6 us per loop
On 6 March 2013 21:16, Benjamin Root ben.r...@ou.edu wrote:
On Tue, Mar 5, 2013 at 9:15 AM, Phil Elson pelson@gmail.com wrote:
The ticket https://github.com/numpy/numpy/issues/2269 discusses the
possibility
The ticket https://github.com/numpy/numpy/issues/2269 discusses the
possibility of implementing a find first style function which can
optimise the process of finding the first value(s) which match a predicate
in a given 1D array. For example:
a = np.sin(np.linspace(0, np.pi, 200))
print
